Indian Crop Insurance and Moral Hazard: Empirical Analysis

Overview

This repository contains the dataset and scripts used for my senior-year dissertation, in which I scraped historical Indian meteorological data in Python and constructed an original empirical framework to evaluate the existence of moral hazard within the Indian crop insurance system. The modeling and analysis were conducted in STATA, and data preprocessing was performed using R.

Contents

• Data Files: Includes all compiled datasets used in the analysis.
• dissdata.R: Scripts to clean, merge, and preprocess the datasets.
• DissData1.dta: Empirical modeling framework and analysis.
• scrape_rainfall.py: Scrapes historical rainfall data from CRIS - India Meteorological Department (https://hydro.imd.gov.in/hydrometweb/DistrictRaifall.aspx)

Requirements

To run the provided scripts, you will need the following packages:

R Packages

• tidyverse
• readxl
• stringr
• dplyr
• stringdist
• expss

Python Packages

• requests
• lxml
• json
• pandas
• openpyxl

Data Sources

• Indian Meteorological Department (IMD) – Historical rainfall and temperature data.
• ICRISAT District-Level Data – Agricultural production statistics.
• PMFBY Indian Crop Insurance Data – Insurance coverage and claim information.